The software analyzes chest CT scans and uses in-depth learning algorithms to accurately diagnose the disease. With an accuracy rate of 97.86%, it is currently the most successful diagnostic tool COVID-19 from the world.
Currently, the diagnosis of COVID-19 is based on nucleic acid testing or PCR tests, as they are commonly known. These tests can produce false negative results, and they can also be affected by hysteresis, when the physical effects of a disease occur longer after infection, or even different from the classic ones.
Therefore, artificial intelligence provides an opportunity to quickly and efficiently monitor large-scale COVID-19 cases, reducing the burden on physicians.
Professor Yudong Zhang, Professor of Knowledge Discovery and Machine Learning at the University of Leicester, says that “their research focuses on the automatic diagnosis of COVID-19 based on the graphical random neural network.
The results showed that our method can automatically find suspicious regions in chest images and make accurate predictions based on representations.
The accuracy of the system means that it can be used in the clinical diagnosis of COVID-19, which can help control the spread of the virus.
The software, which can be implemented even in portable devices such as smartphones, will also be adapted and expanded to detect and diagnose other diseases (such as breast cancer, Alzheimer’s disease and cardiovascular disease). .